We have over 40 user accounts representing numerous NIMH, NINDS and NIDCD protocols. There is continual interest from additional groups that are working on protocols and planning studies. The MEG Core staff has been working interactively with these users in terms of study design, task programming development, acquisition protocols, and signal processing and data analysis. Procedures have been setup for data security, transfer and storage. A substantial Policy and Procedures Manual has been established. We have also worked with the Scientific and Statistical Computing Core to enable transfer of CTF MEG files to AFNI and developed tools for group statistical analysis. Technical and scientific results have been excellent. Signal analysis development includes event-related SAM (synthetic aperture magnetometry) and 275 channel ICA (independent component analysis). Development of time-frequency analysis methods has included Stockwell and wavelet transforms as well as multi-taper techniques. Of particular interest is coherence analysis of virtual channels as a method to investigate interacting brain regions. Staff are working with other MEG groups to integrate several signal processing packages including FieldTrip, NUTMEG and BrainStorm. The goal is to have a unified tool package with a user-friendly interface available to the user community. The SAM software has been successfully run on the Biowulf Cluster allowing for tremendous increase in computing power. A subject eye movement system has been integrated with task presentation software allowing for interactive monitoring of eye position during visual stimulation. The ability to localize not only cortial surface sources but deeper structures has been demonstrated. For a working memory task MEG activation patterns for beta band have shown exceptional agreement with fMRI (functional magnetic resonance imaging) results in the same subject group. Beta desynchronization patterns agree highly with the network of bilateral DLPFC (dorsolateral prefrontal cortex) and posterior parietal cortex seen during working memory in fMRI tasks. Qian Lou and James Blair in an earlier study examining the neural dynamics of facial threat processing have been able to utilize the fine temporal resolution of MEG to learn that there are brian related responses in the amygdale even earlier than in the visual cortex. This supports the suggestion of quick processing route in the brain specific to fear expressions. Understanding these brain mechanisms will be important to further study in mood and affective disorders. They have followed with an investigation of the relation of visual awareness and gamma band signals. Brian Cornwell, Christion Grillion and colleagues have examined how individuals become sensitized to novel stimuli when there are environmental changes that cause anxiety. Using MEG they were able to outline the pathways where brain responses were enhanced to sounds when under threat compared to no threat. These areas included amygdale and insula. Knowledge of these pathways and how they become sensitized may be important for understanding sensitization in disorders such as PTSD (post-traumatic stress disorder). They have followed up to demonstrate that MEG can reliably discriminate amygdala signals using MEG beamforming techniques. Further studies by Jappe and colleagues have shown how emotion valance affects individual difference in early face recognition area signals. Studying how the brain organizes itself into functional networks is key to understanding normal human cognition as well as when it becomes disordered in mental illness. To this end Bassett and co-workers used the spatial and temporal ability of MEG to study how the brain changes configuration during a motor task compared to when at rest. They found that functional networks were characterized by small-world properties indicating a mix or both local connections and long range connections. They have continued this work to demonstrate that dysfuctional networks can be detected and related to behavioral difference in clinial groups. Rutter et al a have also found differences in resting network patterns in patient groups. On going studies include examining hippocampal function in patients with major depression as well as other brain changes when treated with ketamine. These studies are of particular interest to possibly elucidate the mechanism of the anti-depressant action of ketamine infusion. Recent results have shown that increased anterior cingulate activity may be a biomarker that predicts the rapid antidepressant response to ketamine. This work has now been published and well received.